Sr. Software Engineer II DevOps
Overview
Lead design and operation of cloud infrastructure on AWS to support core SaaS platform and agentic AI services. Build AI/ML infrastructure and monitoring for LLM-powered services. Establish IaC standards using Terraform. Implement observability beyond availability. Support big data pipelines, warehousing, and analytics. Drive disaster recovery and improve infrastructure parity. Lead architecture reviews and innovate on developer experience. This role differs by focusing on scaling autonomous AI agents in regulated insurance workflows.
What You'll Do11
- 1Design and operate cloud infrastructure on AWS supporting core SaaS and agentic AI services ensuring reliability scalability and cost efficiency
- 2Build and maintain AI/ML infrastructure and monitoring for LLM-powered agentic services
- 3Establish IaC standards with Terraform defining environment parity drift detection and automated compliance validation
- 4Implement observability beyond availability including data integrity monitoring SLO frameworks and automated regression detection
- 5Develop deployment automation with pre-deployment verification migration script validation and codified rollback procedures
- 6Support big data infrastructure such as data pipelines warehousing Redshift and analytics tooling for reporting BI and AI training
- 7Implement security and compliance controls for AI workloads in regulated carrier environments covering audit logging access governance and configuration management
- 8Drive environment parity across all infrastructure with automated drift detection and remediation
- 9Improve disaster recovery capabilities through documented DR procedures defined RTOs RPOs and tested recovery runbooks
- 10Lead architecture reviews for new services integrations and AI agent deployments partnering with engineering product and security
- 11Innovate on developer experience reducing friction in testing environments CI/CD pipelines and local development workflows
Requirements18
- 16+ years of DevOps SRE or Platform Engineering experience
- 22+ years building or operating AI/ML infrastructure including model serving inference LLM orchestration or agentic systems
- 3Bachelor's degree in Computer Science Engineering or equivalent
- 4Experience building infrastructure for traditional and AI/ML workloads at a SaaS company
- 5Strong Terraform skills managing state modules and multi-environment configurations
- 6Deep understanding of AWS services such as ECS Lambda SageMaker Bedrock S3 DynamoDB Redshift
- 7Proficiency in infrastructure-as-code with Terraform and knowledge of state management modules
- 8Experience with data pipelines warehousing ETL ELT and analytics at scale
- 9Understanding of observability beyond dashboards focusing on data integrity SLOs error budgets and silent failure detection
- 10Compliance-sensitive environment experience with audit trails access governance and change management
- 11Comfortable operating in fast-moving environments with evolving AI capabilities and regulatory implications
- 12Strong communication skills with engineering and non-technical stakeholders
- 13Track record of leading cross-team technical initiatives and mentoring engineers
- 14Proficiency in Python Go TypeScript or similar language
- 15Experience with container orchestration ECS EKS monitoring platforms Datadog CloudWatch
- 16Familiarity with data infrastructure tools like Redshift Airflow Dagster
- 17Experience in regulated industries such as insurance financial services or healthcare
- 18Curiosity about AI and emerging technologies with judgment to apply them responsibly
Salary Insight
$119 - $221k per year
Location
Required Skills
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